A Modest Update

Point the first -

- It was remarked to me that my occasional overindulgence for parenthetical remarks in my writing suggests that I am secretly a Lisp programmer at heart. I snickered. It does look like an interesting language to learn, though…

Point the second -

- I was reminded of a thoroughly snarky point I had made to some friends a while back. String theory (or whatever your preferred scheme for quantizing gravity and unifying the fundamental forces) can explain physics. But the really interesting stuff will require using physics to explain the laundry list of actual phenomenona that we have on our platter. So learn your statistical mechanics, as you can then do everything from analyze (to one degree or another) magnetic samples, ion channel clusters in membranes, and socioeconomic behavior.

So love your stat mech and cherish the partition function!

Point the third -

- A recent blog post over at Just Like Cooking sparked a comment, harkening back to a brief digression elsewhere last year. I was of course led astray for a bit, and dug up some earlier papers on the topic. Not that my to-do list is by any means feeling underweight, but I feel it could be edifying (and potentially interesting) to try and work through the idea in a manner that would be fairly accessible to a (more) general audience. So less "death by Hamiltonian," and more "spiced up with Hamiltonians," if one will permit that metaphor. Read more!

You Shall Pass!

I saw this paper, and it was just asking be blogged about here. I figured I’d give it a shot.

Disclaimer – Not my work, never met any of the authors (although I’m sure they’re all within six degrees of me scientifically). The paper is open access, which I think is a good policy for me to adhere to in any future efforts along these lines.

Citation: L.A. Clifton, et al. “Low Resolution Structure and Dynamics of a Colicin-Receptor Complex Determined by Neutron Scattering.” The Journal of Biological Chemistry. Vol. 287, No. 1, pp. 337-346; January 2, 2012.

Among the many things that bacteria can do, one of them is knocking off other bacteria. There are a number of ways to go about this critical task, not surprisingly, and one of them involves proteins known as bacteriocins. These are proteins that the bacterium uses to kill off potential competitors, as they typically go after closely related bacteria. In this paper, the authors are focusing on Colicin N (ColN), a bacteriocin produced by E. coli. ColN depolarizes the inner membrane of Gram-negative bacteria by forming pores in the inner membrane, resulting in cell death.

The question the authors address is a fundamental one – how does ColN get past the lipopolysaccarhide-decorated outer membrane of a bacterium? It is ~ 40 kDa in size - so, clearly, not going to be able to easily masquerade as an ion or small molecule and pass unhindered through a pore in the outer membrane. The authors note that past research on ColN demonstrated that it is dependent on the presence of an outer membrane protein, OmpF (or related porins), to be effective. Cells that are OmpF-deficient will not be killed off by ColN. I should note that OmpF is a trimeric porin that permits the passage of ions and small molecules through the outer membrane. It was suggested that ColN could pass through the OmpF pore, but would need to be completely unfolded to do so. So there is clearly something going on here that is interesting.

The paper describes a multipronged approach to this question – the authors integrate microscopy, neutron reflectivity, and small angle neutron scattering (SANS). The authors step through their case – they first present the thin film imaging (Brewster’s angle microscopy) and neutron reflection data for their model of the OmpF/phospholipid monolayer. The microscopy suggests similar stability for the OmpF/phospholipid monolayer, although different topography and compression behavior (the formation of domains appears less evenly distributed in the OmpF/phospholipid monolayer, and there are “kinks” in the isotherm for the phospholipid-only monolayer compared to the OmpF-containing one). The neutron reflection data also seems to support the existence of an OmpF/phospholipid bilayer, despite Fig. 3B being mislabeled by my eye. Normally the neutron “refractive index” - neutron scattering length density, aka nSLD – is plotted as a distance away from some reference (e.g., an easily determined interface or a metal layer on which your sample is ultimately deposited). It seems that is what they intended to write (the x-axis seems to be labeled as such) but is mislabeled with the “Q/A^-1” tag.

In any case, much of biologically-oriented neutron scattering is dependent on the existence of contrast variation in the nSLD. You can purchase deuterated compounds (such as lipids), prepare buffers in deuterium oxide, and even express & purify deuterated proteins. You then mix and match your deuterated and protonated components to see what each component looks like when in complex with everything else. It is a low-resolution means of doing so, but the benefits can outweigh the disadvantages.

The authors move onto the ColN portion of their work, showing the microscopy and neutron reflection data for ColN interacting with the OmpF/lipid monolayer. The time-lapse microscopy of ColN with the pure lipid monolayer and the OmpF/lipid monolayer shows increased image intensity, but appears to “smear” homogeneously with the pure lipid monolayer while forming larger, brighter spots with the OmpF/lipid monolayer. Their analysis of the neutron reflectivity data indicates the presence of the ColN in the same layer with the OmpF, and not just interacting with its surface, as they see in the ColN + pure lipid monolayer sample. Given the contrast variation matching, they state that they are able to see ColN extend as it inserts into the lipid region, suggesting that it is unfolding to some extent. The increase in surface pressure would suggest that it is not going through the OmpF pore but is, instead, inserting into the lipid region next to the OmpF. If it was inserting through the pore channel, the surface pressure might be expected to level off and not keep increasing.

The SANS data round out the story – they’re looking at the ColN/OmpF complex in detergent. (I know, I know.) Anyway, their data-derived model has one of the ColN domains slithering down between the cleft between OmpF monomers, while the remainder of ColN remains protruding outward. If you look at Fig. 6C, the blue distance distribution (where you are only looking at scattering from ColN) has two peaks, one that overlaps with the red trace (where one is only looking at OmpF) and a separate peak. So this at least makes sense. They do discuss the potential for translocation via the pore, and some recent literature on that possibility.

Mostly, I thought that this was a really interesting bit of research – while there is the obligatory mention of potential application to antibiotic development, it’s pretty obvious that the fundamental scientific question of “how does a largish protein get across a cell membrane where the cell has no interest in letting it inside?” I think that the experiments were reasonable, were carefully done, and did not set off too many massive alarms in my brain while reading. I would like to think that you could use something like nanodiscs or bicelles for the SANS studies so you could at least approximate a native membrane environment – clearly, sample homogeneity is a concern, as scattering methods can be notoriously sensitive. (Did I ever tell you about the time I spent a good afternoon into evening washing banjo cells for SANS experiments since said cells were just disgusting?) I haven’t worked with nanodiscs – although I’ve heard and read more than I can shake a stick at - and my experience with bicelles hasn’t been quite so detail-oriented, so maybe it would require sublime experimental mastery beyond the typical.*

Anyway. That was kind of fun. Also, how many of you saw Ohm’s Law Survives to the Atomic Scale? I imagine people will want to confirm this, as it is definitely seems really cool. Clearly, it was custom-made by “hand” (well, scanning tunneling microscope), so no immediate applications to large-scale mass production any week soon, but that isn’t why we do science.

Now, off to think about thermodynamics for a while. I need to come up with a reasonable explanation of some data today….. Read more!

The End Draws Near....

....for 2011, at least.

I really don’t have much to add about the recent charges in the UCLA lab safety case, especially given the posts elsewhere (most of which are collected at The Safety Zone here: 1; 2; 3 ). As I can easily count the small molecule syntheses I’ve done since my undergraduate days on my hands with room to spare, I am definitely not someone who can offer hard-earned advice on safety in synthetic chemistry labs based on extensive personal experience.

I will note that – obviously due to my biological inclinations – that lab safety can be just as much as insulating your experiment from you as protecting you from any hazards. Which, given one’s perspective on human nature, might be a more effective means of motivating compliance with lab safety standards.

Onto cheerier subjects….

My plan to bring up Helmholtz when Gibbs is mentioned did not quite pan out this year. I don’t think it’s going to happen. I’ll have to be contrary in some other manner in the future.

I did get back to blogging and commenting a bit this year, and I intend to keep it up next year. While the notion of doing substantive ResearchBlogging is a reasonable one, it would entail winding back the semi-regular sarcasm a bit for thoughtful commentary. I’m not sure if my system could endure the shock. It might happen, though. Having said that, if one has any substantive questions where my thoughts might be of interest, ask away.

Best wishes to all for a happy, healthy, and productive New Year! Read more!

Trust but verify.

The question of how much to trust computational methods is brought up here at Chemiotics II. My answer is that it depends on what one is looking for in the first place.

If one is looking for some sort of completely accurate and precise way to have all biological phenomenona fall out of "first principles," well, I wouldn't hold my breath. Of course, I don't think anyone is really waiting for that. At least I hope not. I believe my feelings on these sorts of issues are best described by personal experiences I've had with computational methods.

In grad school, I had an interest in this one mid-sized protein (somewhere between 40 to 60 kDa) that was known to bind this particular ligand. There was a crystal structure of the protein with and without ligand, although of course it was hardly the entire story (which is why it was the subject of my research attentions). In any case, collaborators did some MD simulations, and it was consistent with what we had found and was known. In their next bit of work, they mentioned that they found something new regarding the mechanism of ligand binding. This was going on the same time as I was doing some work, and as it turned out, my data did not rule it out. And so new research was inspired for those who took up the project after I left.

Currently, I am embroiled in a sordid and complex tale of transmembrane signaling involving the receptor and varying amounts of soluble cytoplasmic proteins that propagate that signal. There was a fairly recent paper detailing MD studies of the signaling process. Well, part of it, I suppose - huge chunks on either end of the transmembrane receptor were not included, and none of the cytoplasmic proteins that bind and are modified by the receptor were included in the study. Certainly a daring attempt, but it's hard to get too worked up over it when it doesn't resemble anything that I actually work with on a daily basis.

In short....I think properly used, it can be a useful way to bridge what is measured experimentally with the metaphors we use to describe processes. (For example - people love using descriptions involving simple machines, but what is actually measured are thermodynamic or spectroscopic quantities. Of course, "force spectroscopy" looks to change this, but when you yank apart a protein, you are no longer just gently playing around at kT or sub-kT conditions to see what kinds of deformations you get naturally or as a response to some stimulus. Anyway....) Certainly, for small enough systems, I am inclined to give them a proper reading, and in cases where the system might be larger but is somewhat well characterized, the same applies. In giant systems where they toss out a number of critical components or oversimplify to the point of absurdity, I am generally far more skeptical.

Merry Christmas to those who celebrate, Happy Hanukkah to those who celebrate, and a delightful winter holiday season to the rest. Read more!

Chemists, controls, and computing.

I have no experience with drug discovery, so I suggest one reads the excellent commentary offered over at The Curious Wavefunction and In the Pipeline inspired by a recent article on the role of computer simulation in pharmaceutical research, presuming that they haven’t already done so. What I thought was interesting enough to post about in response is in Wavefunction’s blog post.

They are reluctant to carry out the kind of basic measurements … which would be enormously valuable in benchmarking modeling techniques.

Methods development research can be difficult to support. Even obtaining modest funding can be difficult. It’s one reason why it can usually seem incremental in nature, as it’s easier to scrounge a few small devices or specialty materials to use with existing research infrastructure. This one is near and dear to my heart, as I have two such projects going on at the moment, and a third which is still in the planning stages. Unfortunately, it’s not the kind of stuff one could convince people it needs to be funded and generously at that. That was really more just me griping. But that is par for the course for me here at my blog…..

Unlike chemists, engineers are usually more naturally inclined to learn programming and mathematical modeling. Most engineers I know know at least some programming. Even if they don't extensively write code they can still use Matlab or Mathematica, and this is independent of their specialty (mechanical, civil, electrical etc.). …The lesson to be drawn here is that programming, simulation and better mathematical grounding need to be more widely integrated in the traditional education of chemists of all stripes, especially those inclined toward the life sciences.

I of course agree, but am inclined to mention a few things. This may be an artifact from my recollection/experience and is no longer the case, but I’ve seen a tendency for computational methods & applications courses intended for chemists to be heavy on the typical computational chemistry aspects (basic electronic structure calculations, a dash of MD, some molecular mechanics) along with a fair bit of introductory programming. Not that there’s anything wrong with that….but wait, actually, it is problematic.

I would think a more useful course might still contain some introductory programming and some of the typical computational chemistry, but I’d like to think that one could also take the time to introduce the students to chemo/bioinformatics as well as a module on proper data fitting. Of course, it might be claimed that it’s better suited for an upper-division chemistry laboratory, which would be fine. The important thing is to get people weaned from MS Excel and to actually start fitting data, not algebraically torturing your data until it’s in a format that can be linearly plotted and then fit with Excel.

Also, given that I have this notion of this course being something that all students will probably find useful in the future, the programming and software elements should be those that will easily lend themselves to a broad range of applications and uses in the future. I would imagine that introducing students to something like Origin or Igor Pro would be useful, as well as (re)introducing them to Mathematica, Matlab, Maple, or other comparable software. While the power of Fortran is well established for the numerical-heavy applications in computational sciences, I feel it would be better to have students introduced to something like Python. You can leave the Fortran for those who want to do the computationally intensive theoretical chemistry, while I’m sure the majority can use Python as a useful tool in their work.

This above is clearly influenced by personal biases (I'm a bio/physical chemist who is in the process of adding "systems biologist" if he keeps it up for much longer), but I think that sort of mix in a "computers & chemistry" course would serve a good cross-section of the chemical community. Any and all commentary, feedback, suggestions, and brutal eviscerations of my points are welcomed. Read more!

Cackling in Glee.

I actually can't muster up any of my lazy man's wit for this year's chemistry Prize - is it physics? Physical chemistry? Materials science? Just sublimely wonderful and scoffs at the narrow cognitive categories that spring up on occasion. It also emphasizes that as chemists, we have fellow travelers in numerous allied pursuits - remember, if we want to continue blaring the "we are the central science" mantra, we have to recognize chemistry of all sorts whatever its ostensible classification.

The comments at ChemBark brought up two questions in my mind -

(1) - what do we consider chemistry?

and

(2) - why did it seemingly not catch anyone's attention as a candidate for the Chemistry Prize?

I've mentioned - in the vein of Roald Hoffmann - that chemistry stands on the pillars of structure, reactivity, and synthesis. Anything that causes us to reevaluate our understanding of even one of those pillars is noteworthy, as quasicrystals surely did in terms of understanding structure. That they can also occur naturally would indicate that our understanding of geochemistry can stand some fleshing out.

Now, if you had asked me about quasicrystals yesterday, I'd have thought that they'd be a Physics Prize one of these years, given that most of what I had heard about them was through physics seminars I'd attended over the years. But it used to be that the gap between physics and chemistry was far smaller - Rutherford (he of the physics vs. stamp collecting joke) picked up his Nobel in Chemistry way back when, and van der Waals was a Physics laureate. This year's Prize is a nice throwback in that regard. I think there might also be something to the comments on ChemBark that solid state chemistry is something of an underexposed topic in undergraduate curricula here in the US, and many of us just don't have that proper background in the field (which is certainly my case - most of what I know is because I stumbled into having learn something about the field in grad school). There might also be an echo chamber effect going on in the chemistry blogosphere. ;)

Now to start preparing for next year's betting pool! Read more!

Nobel Notes

Thumbs up to the Nobel Foundation for their decision regarding Ralph Steinman's laureate status. I always felt that the rule was to make sure nominations of those who have passed on were not submitted in the first place. Now, whether or not one agrees with this is a separate issue.

Given that my professional interests are not very immunological or astrophysical, I don't have any particularly incisive commentary about the Physiology/Medicine or Physics Prizes.

A followup to a comment elsewhere - Tom Wainwright passed away in 2007, so unfortunately he would be ineligible for a Nobel. Given that Aneesur Rahman and George Vineyard have also passed on, Alder is really the only "founding father" of MD who would be a possibility.

On the off chance it is a magnetic resonance Chemistry Prize this year, I will not be sarcastic and post "but it's just applied physics! Why are applied physicists winning Nobel Prizes?" I'll actually just write a short blurb on what was so cool about the new laureates' research. (All other fields of physical chemistry being recognized are fair game for such commentary, though.) Read more!